Displacement-related stressors in a Sri Lankan war-affected community: Identifying the impact of war exposure and ongoing stressors on trauma symptom severity
Bibliographic record
Abstract
In recent years, there has been a shift in the literature towards identifying how ongoing stress adversely affects mental health beyond the effect of direct exposure to war-related violence. The goal of the current study was to investigate the relationship between displacement-related stressors and trauma symptom severity. Participants (N = 1015) were recruited from primary healthcare clinics (PHCs) in Northern Sri Lanka and completed a demographic and displacement history questionnaire, the Stressful Life Events Checklist, and the Harvard Trauma Questionnaire. Four latent stressor constructs were identified through exploratory and confirmatory factor analyses: 1) personal safety concerns; 2) war-related loss; 3) material loss, and 4) personal hardships. Structural equation modeling was used to examine the relationship between stressors and trauma symptom severity. In the final structural equation model, war-related loss and material loss were positively related to symptom severity whereas psychosocial hardship was found to be negatively related to symptom severity. Results highlight how an integrated model of mental health can more fully inform the needs stemming from displacement-related stressors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".